Search results for: surface damage detection

Authors: N. Nowzari-Dalini, S. Sabbaghi

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Phenol is a hazardous material found in many industrial wastewaters. Photocatalytic degradation and furthermore catalyst doping are promising techniques in purpose of effective phenol removal, which have been studied comprehensively in this decade. In this study, Fe, Cr codoped TiO₂ were prepared by sol-gel method, and its photocatalytic activity was investigated through degradation of phenol under visible light. The catalyst was characterized by XRD, SEM, FT-IR, BET, and EDX. The results showed that nanoparticles possess anatase phase, and the average size of nanoparticles was about 21 nm. Also, photocatalyst has significant surface area. Effect of experimental parameters such as pH, irradiation time, pollutant concentration, and catalyst concentration were investigated by using Design-Expert^® software. 98% of phenol degradation was achieved after 6h of irradiation.

Keywords: doping, metals, sol-gel, titanium dioxide, wastewater

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Authors: Bienvenu Gael Fouda Mbanga, Zikhona Tywabi-Ngeva, Kriveshini Pillay

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This work highlighted a new method for preparing Nitrogen carbon nanoparticles fused on zinc oxide nanoparticle nanocomposite (N-CNPs/ZnONPsNC) to remove copper ions (Cu²+) from wastewater by sol-gel method and applying the metal-loaded adsorbent in latent fingerprint application. The N-CNPs/ZnONPsNC showed to be an effective sorbent for optimum Cu²+ sorption at pH 8 and 0.05 g dose. The Langmuir isotherm was found to best fit the process, with a maximum adsorption capacity of 285.71 mg/g, which was higher than most values found in other research for Cu²+ removal. Adsorption was spontaneous and endothermic at 25oC. In addition, the Cu²+-N-CNPs/ZnONPsNC was found to be sensitive and selective for latent fingerprint (LFP) recognition on a range of porous surfaces. As a result, in forensic research, it is an effective distinguishing chemical for latent fingerprint detection.

Keywords: latent fingerprint, nanocomposite, adsorption, copper ions, metal loaded adsorption, adsorbent

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Authors: Arindam Chaudhuri

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Classification of data has been actively used for most effective and efficient means of conveying knowledge and information to users. The prima face has always been upon techniques for extracting useful knowledge from data such that returns are maximized. With emergence of huge datasets the existing classification techniques often fail to produce desirable results. The challenge lies in analyzing and understanding characteristics of massive data sets by retrieving useful geometric and statistical patterns. We propose a supervised parallel fuzzy rough support vector machine (PFRSVM) for data classification in cloud environment. The classification is performed by PFRSVM using hyperbolic tangent kernel. The fuzzy rough set model takes care of sensitiveness of noisy samples and handles impreciseness in training samples bringing robustness to results. The membership function is function of center and radius of each class in feature space and is represented with kernel. It plays an important role towards sampling the decision surface. The success of PFRSVM is governed by choosing appropriate parameter values. The training samples are either linear or nonlinear separable. The different input points make unique contributions to decision surface. The algorithm is parallelized with a view to reduce training times. The system is built on support vector machine library using Hadoop implementation of MapReduce. The algorithm is tested on large data sets to check its feasibility and convergence. The performance of classifier is also assessed in terms of number of support vectors. The challenges encountered towards implementing big data classification in machine learning frameworks are also discussed. The experiments are done on the cloud environment available at University of Technology and Management, India. The results are illustrated for Gaussian RBF and Bayesian kernels. The effect of variability in prediction and generalization of PFRSVM is examined with respect to values of parameter C. It effectively resolves outliers’ effects, imbalance and overlapping class problems, normalizes to unseen data and relaxes dependency between features and labels. The average classification accuracy for PFRSVM is better than other classifiers for both Gaussian RBF and Bayesian kernels. The experimental results on both synthetic and real data sets clearly demonstrate the superiority of the proposed technique.

Keywords: FRSVM, Hadoop, MapReduce, PFRSVM

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Authors: Mara Getachew Zenebe, Luuk Fleskens, Abdu Obieda Ahmed

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This paper seeks to advance our scientific understanding of optimizing flood utilization in regions impacted by climate change, with a focus on enhancing agricultural productivity through effective irrigation management. The study was conducted as part of a three-year (2021 to 2023) USAID-supported initiative aimed at promoting Economic Growth and Peace in the Gash Agricultural Scheme (GAS), situated in Sudan's water-stressed Eastern region. GAS is the country's largest flood-irrigated scheme, covering 100,800 hectares of cultivable land, with a potential to provide the food security needs of over a quarter of a million agro-pastoral community members. GAS relies on the Gash River, which sources its water from high-intensity rainfall events in the highlands of Ethiopia and Eritrea. However, climate change and variations in these highlands have led to increased variability in the Gash River's flow. The study conducted water balance analyses based on a ten-year dataset of the annual Gash River flow, irrigated area; as well as the evapotranspiration demand of the major sorghum crop. Data collection methods included field measurements, surveys, remote sensing, and CropWat modelling. The water balance assessment revealed that the existing three-year rotation-based irrigation system management, capping cultivated land at 33,000 hectares annually, is excessively risk-averse. While this system reduced conflicts among the agro-pastoral communities by consistently delivering on the land promised to be annually cultivated, it also increased GAS's vulnerability to flood damage due to several reasons. The irrigation efficiency over the past decade was approximately 30%, leaving significant unharnessed floodwater that caused damage to infrastructure and agricultural land. The three-year rotation resulted in inadequate infrastructural maintenance, given the destructive nature of floods. Additionally, it led to infrequent land tillage, allowing the encroachment of mesquite trees hindering major sorghum crop growth. Remote sensing data confirmed that mesquite trees have overtaken 70,000 hectares in the past two decades, rendering them unavailable for agriculture. The water balance analyses suggest shifting to a two-year rotation, covering approximately 50,000 hectares annually while maintaining risk aversion. This shift could boost GAS's annual sorghum production by two-thirds, exceeding 850,000 tons. The scheme's efficiency can be further enhanced through low-cost on-farm interventions. Currently, large irrigation plots that range from 420 to 756 hectares are irrigated with limited water distribution guidance, leading to uneven irrigation. As demonstrated through field trials, implementing internal longitudinal bunds and horizontal deflector bunds can increase adequately irrigated parts of the irrigation plots from 50% to 80% and thus nearly double the sorghum yield to 2 tons per hectare while reducing the irrigation duration from 30 days to a maximum of 17 days. Flow measurements in 2021 and 2022 confirmed that these changes sufficiently meet the sorghum crop's water requirements, even with a conservative 60% field application efficiency assumption. These insights and lessons from the GAS on enhancing agricultural resilience and sustainability in the face of climate change are relevant to flood-based livelihood systems globally.

Keywords: climate change, irrigation management and productivity, variable flood flows, water balance analysis

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Authors: Wahyu Purnama Putra, Artono Isharanto

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Thoracic trauma is trauma that hits the thoracic wall or intrathoracic organs, either due to blunt trauma or sharp trauma. Thoracic trauma often causes impaired ventilation-perfusion due to damage to the lung parenchyma. This results in impaired tissue oxygenation, which is one of the causes of acute respiratory distress syndrome (ARDS). These changes are caused by the release of pro-inflammatory mediators, plasmatic proteins, and proteases into the alveolar space associated with ongoing edema, as well as oxidative products that ultimately result in severe inhibition of the surfactant system. This study aims to predict the incidence of acute respiratory distress syndrome (ARDS) through human neutrophil elastase levels. This study examines the relationship between plasma elastase levels as a predictor of the incidence of ARDS in thoracic trauma patients in Malang. This study is an observational cohort study. Data analysis uses the Pearson correlation test and ROC curve (receiver operating characteristic curve). It can be concluded that there is a significant (p= 0.000, r= -0.988) relationship between elastase levels and BGA-3. If the value of elastase levels is limited to 23.79 ± 3.95, the patient will experience mild ARDS. While if the value of elastase levels is limited to 57.68 ± 18.55, in the future, the patient will experience moderate ARDS. Meanwhile, if the elastase level is between 107.85 ± 5.04, the patient will likely experience severe ARDS. Neutrophil elastase levels correlate with the degree of severity of ARDS incidence.

Keywords: ARDS, human neutrophil elastase, severity, thoracic trauma

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Authors: Kent Salomonsson, Xuefang Zhao, Sara Kallin

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Human soft tissue is loaded and deformed by any activity, an effect known as a stress-strain relationship, and is often described by a load and tissue elongation curve. Several advances have been made in the fields of biology and mechanics of soft human tissue. However, there is limited information available on in vivo tissue mechanical characteristics and behavior. Confident mechanical properties of human soft tissue cannot be extrapolated from e.g. animal testing. Thus, there is need for non invasive methods to analyze mechanical characteristics of soft human tissue. In the present study, the internal mechanical conditions of the lower limb, which is subject to an external load, is studied by use of the finite element method. A detailed finite element model of the lower limb is made possible by use of MRI scans. Skin, fat, bones, fascia and muscles are represented separately and the material properties for them are obtained from literature. Previous studies have been shown to address macroscopic deformation features, e.g. indentation depth, to a large extent. However, the detail in which the internal anatomical features have been modeled does not reveal the critical internal strains that may induce hypoxia and/or eventual tissue damage. The results of the present study reveals that lumped material models, i.e. averaging of the material properties for the different constituents, does not capture regions of critical strains in contrast to more detailed models.

Keywords: FEM, tissue, indentation, properties

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Authors: Rafael Ricieri, Rogerio Barros

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Objective: This study is to report a case of massive necrotizing enterocolitis in a six-month-old patient, requiring ileostomy and protective jejunostomy as a damage control measure in the first exploratory laparotomy surgery in massive enterocolitis without a previous diagnosis. Methods: This study is a case report of success in making and closing a protective jejunostomy. However, the low number of publications on this staged and risky measure of surgical resolution encouraged the team to study the indication and especially the correct time for closing the patient's protective jejunostomy. The main study instrument will be the six-month-old patient's medical record. Results: Based on the observation of the case described, it was observed that the time for the closure of the described procedure (protective jejunostomy) varies according to the level of compromise of the health status of your patient and of an individual of each person. Early closure, or failure to close, can lead to a favorable problem for the patient since several problems can result from this closure, such as new intestinal perforations, hydroelectrolyte disturbances. Despite the risk of new perforations, we suggest closing the protective jejunostomy around the 14th day of the procedure, thus keeping the patient on broad-spectrum antibiotic therapy and absolute fasting, thus reducing the chances of new intestinal perforations. Associated with the closure of the jejunostomy, a gastric tube for decompression is necessary, and care in an intensive care unit and electrolyte replacement is necessary to maintain the stability of the case.

Keywords: jejunostomy, ileostomy, enterocolitis, pediatric surgery, gastric surgery

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Authors: Daniel Bulanda, Janusz A. Starzyk, Adrian Horzyk

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The electrocardiogram (ECG) is one of the most commonly used medical tests, essential for correct diagnosis and treatment of the patient. While ECG devices generate a huge amount of data, only a small part of them carries valuable medical information. To deal with this problem, many compression algorithms and filters have been developed over the past years. However, the rapid development of new machine learning techniques poses new challenges. To address this class of problems, we created the FlexPoints algorithm that searches for characteristic points on the ECG signal and ignores all other points that do not carry relevant medical information. The conducted experiments proved that the presented algorithm can significantly reduce the number of data points which represents ECG signal without losing valuable medical information. These sparse but essential characteristic points (flex points) can be a perfect input for some modern machine learning models, which works much better using flex points as an input instead of raw data or data compressed by many popular algorithms.

Keywords: characteristic points, electrocardiogram, ECG, machine learning, signal compression

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Authors: Jinsiang Shaw, Pik-Hoe Chen

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This paper aims to integrate human recognition, motion recognition, and object tracking technologies without requiring a pre-training database model for motion recognition or the unknown object itself. Furthermore, it can simultaneously track multiple users and multiple objects. Unlike other existing human motion recognition methods, our approach employs a rule-based condition method to determine if a user hand is approaching or departing an object. It uses a background subtraction method to separate the human and object from the background, and employs behavior features to effectively interpret human object-grabbing actions. With an object’s histogram characteristics, we are able to isolate and track it using back projection. Hence, a moving object trajectory can be recorded and the object itself can be located. This particular technique can be used in a camera surveillance system in a shopping area to perform real-time intelligent surveillance, thus preventing theft. Experimental results verify the validity of the developed surveillance algorithm with an accuracy of 83% for shoplifting detection.

Keywords: Automatic Tracking, Back Projection, Motion Recognition, Shoplifting

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Authors: Victorita Radulescu

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Introduction: The optimum exploitation of agricultural land in the presence of an aquifer polluted by the surface sources requires close monitoring of groundwater level in both periods of intense irrigation and in absence of the irrigations, in times of drought. Currently in Romania, in the south part of the country, the Baragan area, many agricultural lands are confronted with the risk of groundwater pollution in the absence of systematic irrigation, correlated with the climate changes. Basic Methods: The non-steady flow of the groundwater from an aquifer can be described by the Bousinesq’s partial differential equation. The finite element method was used, applied to the porous media needed for the water mass balance equation. By the proper structure of the initial and boundary conditions may be modeled the flow in drainage or injection systems of wells, according to the period of irrigation or prolonged drought. The boundary conditions consist of the groundwater levels required at margins of the analyzed area, in conformity to the reality of the pollutant emissaries, following the method of the double steps. Major Findings/Results: The drainage condition is equivalent to operating regimes on the two or three rows of wells, negative, as to assure the pollutant transport, modeled with the variable flow in groups of two adjacent nodes. In order to obtain the level of the water table, in accordance with the real constraints, are needed, for example, to be restricted its top level below of an imposed value, required in each node. The objective function consists of a sum of the absolute values of differences of the infiltration flow rates, increased by a large penalty factor when there are positive values of pollutant. In these conditions, a balanced structure of the pollutant concentration is maintained in the groundwater. The spatial coordinates represent the modified parameters during the process of optimization and the drainage flows through wells. Conclusions: The presented calculation scheme was applied to an area having a cross-section of 50 km between two emissaries with various levels of altitude and different values of pollution. The input data were correlated with the measurements made in-situ, such as the level of the bedrock, the grain size of the field, the slope, etc. This method of calculation can also be extended to determine the variation of the groundwater in the aquifer following the flood wave propagation in envoys.

Keywords: environmental protection, infiltrations, numerical modeling, pollutant transport through soils

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Authors: Dhruvit S. Berawala, Jann R. Ursin, Obrad Slijepcevic

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Shale gas is one of the most rapidly growing forms of natural gas. Unconventional natural gas deposits are difficult to characterize overall, but in general are often lower in resource concentration and dispersed over large areas. Moreover, gas is densely packed into the matrix through adsorption which accounts for large volume of gas reserves. Gas production from tight shale deposits are made possible by extensive and deep well fracturing which contacts large fractions of the formation. The conventional reservoir modelling and production forecasting methods, which rely on fluid-flow processes dominated by viscous forces, have proved to be very pessimistic and inaccurate. This paper presents a new approach to forecast shale gas production by detailed modeling of gas desorption, diffusion and non-linear flow mechanisms in combination with statistical representation of these processes. The representation of the model involves a cube as a porous media where free gas is present and a sphere (SiC: Sphere in Cube model) inside it where gas is adsorbed on to the kerogen or organic matter. Further, the sphere is considered consisting of many layers of adsorbed gas in an onion-like structure. With pressure decline, the gas desorbs first from the outer most layer of sphere causing decrease in its molecular concentration. The new available surface area and change in concentration triggers the diffusion of gas from kerogen. The process continues until all the gas present internally diffuses out of the kerogen, gets adsorbs onto available surface area and then desorbs into the nanopores and micro-fractures in the cube. Each SiC idealizes a gas pathway and is characterized by sphere diameter and length of the cube. The diameter allows to model gas storage, diffusion and desorption; the cube length takes into account the pathway for flow in nanopores and micro-fractures. Many of these representative but general cells of the reservoir are put together and linked to a well or hydraulic fracture. The paper quantitatively describes these processes as well as clarifies the geological conditions under which a successful shale gas production could be expected. A numerical model has been derived which is then compiled on FORTRAN to develop a simulator for the production of shale gas by considering the spheres as a source term in each of the grid blocks. By applying SiC to field data, we demonstrate that the model provides an effective way to quickly access gas production rates from shale formations. We also examine the effect of model input properties on gas production.

Keywords: adsorption, diffusion, non-linear flow, shale gas production

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Authors: Ayman Abd-Elhamed, Sayed Mahmoud

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The present research work investigates the seismic response of reinforced concrete (RC) frame building considering the effect of modeling masonry infill (MI) walls. The seismic behavior of a residential 6-storey RC frame building, considering and ignoring the effect of masonry, is numerically investigated using response spectrum (RS) analysis. The considered herein building is designed as a moment resisting frame (MRF) system following the Egyptian code (EC) requirements. Two developed models in terms of bare frame and infill walls frame are used in the study. Equivalent diagonal strut methodology is used to represent the behavior of infill walls, whilst the well-known software package ETABS is used for implementing all frame models and performing the analysis. The results of the numerical simulations such as base shear, displacements, and internal forces for the bare frame as well as the infill wall frame are presented in a comparative way. The results of the study indicate that the interaction between infill walls and frames significantly change the responses of buildings during earthquakes compared to the results of bare frame building model. Specifically, the seismic analysis of RC bare frame structure leads to underestimation of base shear and consequently damage or even collapse of buildings may occur under strong shaking. On the other hand, considering infill walls significantly decrease the peak floor displacements and drifts in both X and Y-directions.

Keywords: masonry infill, bare frame, response spectrum, seismic response

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Authors: El Oualid Mokhnache, Noureddine Ramdani

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The choice of gun barrel materials is crucial to ensure the maximum high rate of fire. The high rate of fire causes wear-out damage and shuts off mechanical properties (hardness, strength, wear resistance, etc.) and ballistic properties (bullet speed, dispersion and precision, longevity of barrel, etc). To overcome these kinds of problems, a deep understanding of the effect of the firing cycle on the mechanical and ballistic properties of the barrel is regarded as crucial to improving its characteristics. In the present work, a real experimental test of firing by using a high steel barrel with 7.62x39 ammunition was carried. Microstructural observations by using SEM were investigated. Hardness evolution through the barrel of both barrels labeled as reference barrels and as fired barrels were compared and discussed. Ballistic properties during the firing test, including speed of projectile and precision dispersion, are revealed and discussed as well. The aim of the present communication is about to discuss the relationship between pressure distribution versus mechanical properties through the wall barrel. Ballistic properties, including speed of the projectile, dispersion, and precision results during the shooting process, were investigated. Microstructure observations of the as-rifled barrel in comparison with the as-reference barrel were performed as well.

Keywords: barrel, ballistic, pressure, microstructure evolution, hardness

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Authors: Mecheri Zeid Belmecheri, Maamar Ahfir, Izzet Kale

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Automatic cardiac auscultation is still a subject of research in order to establish an objective diagnosis. Recorded heart sounds as Phonocardiogram signals (PCG) can be used for automatic segmentation into components that have clinical meanings. These are the first sound, S1, the second sound, S2, and the systolic and diastolic components, respectively. In this paper, an automatic method is proposed for the robust segmentation of heart sounds. This method is based on calculating an intermediate sawtooth-shaped signal from the length variation of the recorded Phonocardiogram (PCG) signal in the time domain and, using its positive derivative function that is a binary signal in training a Recurrent Neural Network (RNN). Results obtained in the context of a large database of recorded PCGs with their simultaneously recorded ElectroCardioGrams (ECGs) from different patients in clinical settings, including normal and abnormal subjects, show a segmentation testing performance average of 76 % sensitivity and 94 % specificity.

Keywords: heart sounds, PCG segmentation, event detection, recurrent neural networks, PCG curve length

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Authors: Sana Rezig, Yosr Ben Mlik, Mounir Jaouadi, Foued Khoffi, Slah Msahli, Bernard Durand

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Increasing interest in environmental concerns, natural fibers are once again being considered as reinforcements for polymer composites. The main objective of this study is to explore another natural resource, Typha fiber; which is renewable without production cost and available abundantly in nature. The aim of this study was to study the flexural properties of composite resin with and without reinforcing Typha leaf and stem fibers. The specimens were made by the hand-lay-up process using polyester matrix. In our work, we focused on the effect of various treatment conditions (sea water, alkali treatment and a combination of the two treatments), as a surface modifier, on the flexural properties of the Typha fibers reinforced polyester composites. Moreover, weight ratio of Typha leaf or stem fibers was investigated. Besides, both fibers from leaf and stem of Typha plant were used to evaluate the reinforcing effect. Another parameter, which is reinforcement structure, was investigated. In fact, a first composite was made with air-laid nonwoven structure of fibers. A second composite was with a mixture of fibers and resin for each kind of treatment. Results show that alkali treatment and combined process provided better mechanical properties of composites in comparison with fiber treated by sea water. The fiber weight ratio influenced the flexural properties of composites. Indeed, a maximum value of flexural strength of 69.8 and 62,32 MPa with flexural modulus of 6.16 and 6.34 GPawas observed respectively for composite reinforced with leaf and stem fibers for 12.6 % fiber weight ratio. For the different treatments carried out, the treatment using caustic soda, whether alone or after retting seawater, show the best results because it improves adhesion between the polyester matrix and the fibers of reinforcement. SEM photographs were made to ascertain the effects of the surface treatment of the fibers. By varying the structure of the fibers of Typha, the reinforcement used in bulk shows more effective results as that used in the non-woven structure. In addition, flexural strength rises with about (65.32 %) in the case of composite reinforced with a mixture of 12.6% leaf fibers and (27.45 %) in the case of a composite reinforced with a nonwoven structure of 12.6 % of leaf fibers. Thus, to better evaluate the effect of the fiber origin, the reinforcing structure, the processing performed and the reinforcement factor on the performance of composite materials, a statistical study was performed using Minitab. Thus, ANOVA was used, and the patterns of the main effects of these parameters and interaction between them were established. Statistical analysis, the fiber treatment and reinforcement structure seem to be the most significant parameters.

Keywords: flexural properties, fiber treatment, structure and weight ratio, SEM photographs, Typha leaf and stem fibers

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Authors: Husham Bayazed, Fatimah Yousif

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Purpose of Presentation: The infant immune system has a reputation for being weak and underdeveloped when compared to the adult immune system, but the comparison isn’t quite fair. At the start, as the COVID-19 pandemic drags on and evolves, many Pediatricians and kids' parents have been left with renewed questions about the consequences and sequel of infection on children and the steps to be taken if their child has the symptoms of COVID-19 or tests positive. Recent Findings Literature reviews and recent studies revealed that children are better than adults at controlling SARS-CoV-2. There was conflicting evidence on age-related differences in ACE2 expression in the nose and lungs. But scientists who measured the ‘viral load’ in children's upper airways have seen no clear difference between children and adults. Moreover, the hypothesis is that kids might be more exposed to other coronaviruses common cold, with a production of ready protective antibodies to lock on to the pandemic coronavirus. But the evidence suggests that adults also have this immunity too. Strikingly, these ‘cross-reactive’ antibodies don’t offer any special protection. Summary One of the few silver linings of the Covid-19 pandemic is that children are relatively spared. The kid's Innate Immunity is hardly the whole story, the innate immune response against SARS-CoV-2 infection is early initiative calm with low immunological tone to prevent an overactive immunity and with rapidly repair damage to the lungs in contrast to stormy waves in adults. Therefore, Kids are at much lower risk of Covid-19 infection, and they are still winning the battle against Covid-19 with their innate immunity.

Keywords: Covid-19, kids, ACE2 receptors, immunity

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Authors: Ayodeji Oluleye

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This study used Total Ozone Mapping Spectrometer (TOMS) Aerosol Index (AI) and reanalysis dataset of thirty years (1983-2012) to investigate the influence of the atmospheric circulation on dust transport during the Harmattan period over WestAfrica using TOMS data. The Harmattan dust mobilization and atmospheric circulation pattern were evaluated using a kernel density estimate which shows the areas where most points are concentrated between the variables. The evolution of the Inter-Tropical Discontinuity (ITD), Sea surface Temperature (SST) over the Gulf of Guinea, and the North Atlantic Oscillation (NAO) index during the Harmattan period (November-March) was also analyzed and graphs of the average ITD positions, SST and the NAO were observed on daily basis. The Pearson moment correlation analysis was also employed to assess the effect of atmospheric circulation on Harmattan dust transport. The results show that the departure (increased) of TOMS AI values from the long-term mean (1.64) occurred from around 21st of December, which signifies the rich dust days during winter period. Strong TOMS AI signal were observed from January to March with the maximum occurring in the latter months (February and March). The inter-annual variability of TOMSAI revealed that the rich dust years were found between 1984-1985, 1987-1988, 1997-1998, 1999-2000, and 2002-2004. Significantly, poor dust year was found between 2005 and 2006 in all the periods. The study has found strong north-easterly (NE) trade winds were over most of the Sahelianregion of West Africa during the winter months with the maximum wind speed reaching 8.61m/s inJanuary.The strength of NE winds determines the extent of dust transport to the coast of Gulf of Guinea during winter. This study has confirmed that the presence of the Harmattan is strongly dependent on theSST over Atlantic Ocean and ITD position. The locus of the average SST and ITD positions over West Africa could be described by polynomial functions. The study concludes that the evolution of near surface wind field at 925 hpa, and the variations of SST and ITD positions are the major large scale atmospheric circulation systems driving the emission, distribution, and transport of Harmattan dust aerosols over West Africa. However, the influence of NAO was shown to have fewer significance effects on the Harmattan dust transport over the region.

Keywords: atmospheric circulation, dust aerosols, Harmattan, West Africa

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Authors: Hamed A. Keykha, Hadi Miri

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This paper describes a new method of soil stabilisation, electro-biogrouting (EBM), for improvement of soft soil with low hydraulic conductivity. This method uses an applied voltage gradient across the soil to induce the ions and bacteria cells through the soil matrix, resulting in CaCO3 precipitation and an increase of the soil shear strength in the process. The EBM were used effectively with two injection methods; bacteria injection and products of bacteria injection. The bacteria cells, calcium ions and urea were moved across the soil by electromigration and electro osmotic flow respectively. The products of bacteria (CO3-2) were moved by electromigration. The results showed that the undrained shear strength of the soil increased from 6 to 65 and 70 kPa for first and second injection method respectively. The injection of carbonate solution and calcium could be effectively flowed in the clay soil compare to injection of bacteria cells. The detection of CaCO3 percentage and its corresponding water content across the specimen showed that the increase of undrained shear strength relates to the deposit of calcite crystals between soil particles.

Keywords: Sporosarcina pasteurii, electrophoresis, electromigration, electroosmosis, biocement

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Authors: Roni Rachel Mendelson, Caileigh Pudela

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Bacillus cereus is a toxin-producing, facultatively anaerobic gram-positive bacterium that is widely distributed environmentally. It can quickly multiply at room temperature with an abundantly present preformed toxin. When ingested, this toxin can cause gastrointestinal illness, which is the commonly known manifestation of the disease. Bacillus cereus sepsis is a disease that is mostly concerning in the population of the immunocompromised patients. One of them is acute lymphoblastic leukemia’s patients during induction. Pediatric acute lymphoblastic leukemia is a common pediatric hematologic malignancy. It is characterized by the rapid proliferation of poorly differentiated lymphoid progenitor cells inside the bone marrow. We present here a 21-month-old boy undergoing induction chemotherapy for acute lymphoblastic leukemia who developed bacillus sepsis bacteremia and, as a result, multi organ failure leading to seizures and multiple strokes. Our case report highlights the extensive overall and neurological damage that can be caused because of bacillus cereus bacteremia, which can lead to higher mortality rate and decreased in survivorship in a highly curable disease. It is very subtle and difficult to recognize and appears to be deteriorating extremely fast. There should be a low threshold for work up and empiric coverage for neutropenic patients during acute lymphoblastic leukemia induction therapy.

Keywords: acute lymphoblastic leukemia, bacillus cereus, immunocompromised, sepsis

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Authors: Saud Hamdan Alshammari

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Photocatalytic water splitting to produce hydrogen (H₂) has obtained significant attention as an environmentally friendly technology. This process, which produces hydrogen from water and sunlight, represents a renewable energy source. Titanium dioxide (TiO₂) plays a critical role in photocatalytic hydrogen production due to its chemical stability, availability, and low cost. Nevertheless, TiO₂'s wide band gap (3.2 eV) limits its visible light absorption and might affect the effectiveness of the photocatalytic. Coupling TiO₂ with other semiconductors is a strategy that can enhance TiO₂ by narrowing its band gap and improving visible light absorption. This paper studies the modification of TiO₂ by coupling it with another semiconductor such as CdS nanoparticles using a reflux reactor and autoclave reactor that helps form a core-shell structure. Characterization techniques, including TEM and UV-Vis spectroscopy, confirmed successful coating of TiO₂ on CdS core, reduction of the band gap from 3.28 eV to 3.1 eV, and enhanced light absorption in the visible region. These modifications are attributed to the heterojunction structure between TiO₂ and CdS.The essential goal of this study is to improve TiO₂ for use in photocatalytic water splitting to enhance hydrogen production. The core-shell TiO₂@CdS nanoparticles exhibited promising results, due to band gap narrowing and improved light absorption. Future work will involve adding Pt as a co-catalyst, which is known to increase surface reaction activity by enhancing proton adsorption. Evaluation of the TiO₂@CdS@Pt catalyst will include performance assessments and hydrogen productivity tests, considering factors such as effective shapes and material ratios. Moreover, the study could be enhanced by studying further modifications to the catalyst and displaying additional performance evaluations. For instance, doping TiO₂ with metals such as nickel (Ni), iron (Fe), and cobalt (Co) and non-metals such as nitrogen (N), carbon (C), and sulfur (S) could positively influence the catalyst by reducing the band gap, enhancing the separation of photogenerated electron-hole pairs, and increasing the surface area, respectively. Additionally, to further improve catalytic performance, examining different catalyst morphologies, such as nanorods, nanowires, and nanosheets, in hydrogen production could be highly beneficial. Optimizing photoreactor design for efficient photon delivery and illumination will further enhance the photocatalytic process. These strategies collectively aim to overcome current challenges and improve the efficiency of hydrogen production via photocatalysis.

Keywords: hydrogen production, photocatalytic, water spliiting, semiconductor, nanoparticles

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Authors: Mahendrasingh J. Pawar, M. D. Gaoner

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Ta-doped Nb2O5 (Ta content 0.5-2% mole fraction) nanoparticles in the range of 20-40 nm were synthesized by combustion technique. The crystalline phase, morphology and size of the nanoparticles were characterized by X-ray diffraction (XRD), transmission electron microscopy (TEM) and UV-vis spectroscopy. The specific surface area of the nanoparticles was measured by nitrogen adsorption (BET analysis). The undoped Nb2O5 nanoparticles were found to have the particles size in the range of 50−80 nm. The photocatalytic performance of the samples was characterized by degrading 20 mg/L toluene under UV−Vis irradiation. The results show that the Ta-doped Nb2O5 nanoparticles exhibit a significant increase in photocatalytic performance over the undoped Nb2O5 nanoparticles, and the Nb2O5 nanoparticles doped with 1.5% Ta and calcined at 450°C show the best photocatalytic performance.

Keywords: Nb2O5, Ta-doped Nb2O5, photodegradation of Toluene, combustion method

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Authors: Maziar Noei

Abstract:

Adsorption of a boron nitride nanotube (BNNT) was examined toward ethylacetylene (C4H6) molecule by using density functional theory (DFT) calculations at the B3LYP/6-31G (d) level, and it was found that the adsorption energy (Ead) of ethylacetylene the pristine nanotubes is about -1.60kcal/mol. But when nanotube have been doped with Si and Al atomes, the adsorption energy of ethylacetylene molecule was increased. Calculation showed that when the nanotube is doping by Al, the adsorption energy is about -24.19kcal/mol and also the amount of HOMO/LUMO energy gap (Eg) will reduce significantly. Boron nitride nanotube is a suitable adsorbent for ethylacetylene and can be used in separation processes ethylacetylene. It is seem that nanotube (BNNT) is a suitable semiconductor after doping, and the doped BNNT in the presence of ethylacetylene an electrical signal is generating directly and therefore can potentially be used for ethylacetylene sensors.

Keywords: sensor, nanotube, DFT, ethylacetylene

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Authors: Mohamed Gar Alalm

Abstract:

This study aims to investigate various operating conditions that affect the performance of the electro-Fenton process for degradation of pesticides. Stainless steel electrodes were utilized in the electro-Fenton cell due to their relatively low cost. The favored conditions of current intensity, pH, iron loading, and pesticide concentration were deeply discussed. Complete removal of pesticide was attained at the optimum conditions. The degradation kinetics were described by pseudo- first-order pattern. In addition, a response surface model was developed to describe the performance of electro-Fenton process under different operational conditions. The model indicated that the coefficient of determination was (R² = 0.995).

Keywords: electro-Fenton, stainless steel, pesticide, wastewater

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Authors: H. Al-Hajeri

Abstract:

The computation of the effectiveness of turbulence enhancement surface features, such as ribs as means of promoting mixing and hence heat transfer, has attracted the continued attention of the engineering community. In this study, the simulation of a three-dimensional cooling passage is carried out employing a number of turbulence models including Durbin model. The cooling passage consists of a square section duct whose upper and lower surfaces feature staggered cuboid ribs. The main objective of this paper is to provide comparisons of the performance of the v2-f model against other established turbulence models as implemented in the commercial CFD code Ansys Fluent. The present study demonstrates that the v2-f model can successfully capture the isothermal air flow phenomena in flow over obstacles.

Keywords: CFD, cooling passage, Durbin model, turbulence model

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Authors: Nabi Ullah

Abstract:

The single-step solvothermal method is used to prepare Cu/CuSe as an electrocatalyst for methanol electro-oxidation reaction (MOR). 1,3-butane-diol is selected as a reaction medium, whose viscosity and complex formation with Cu(II) ions dictate the catalyst morphology. The catalyst has a macroporous structure, which is composed of nanoballs with a high purity, crystallinity, and uniform morphology. The electrocatalyst is excellent for MOR, as it delivers a current density of 37.28 mA/mg at a potential of 0.6 V (vs Ag/AgCl) in the electrolyte of 1 M KOH and 0.75 M methanol at a 50 mV/s scan rate under conditions of cyclic voltammetry. The catalyst also shows good stability for 3600 s with negligible charge transfer resistance and a high electrochemical active surface area (ECSA) value of 0.100 mF/cm².

Keywords: MOR, copper selenide, electocatalyst, energy application

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Authors: Chandra Gupt Porwal

Abstract:

Excessive vibration means increased wear, increased repair efforts, bad product selection & quality and high energy consumption. This may be sometimes experienced by cavitation or suction/discharge re-circulation which could occur only when net positive suction head available NPSHA drops below the net positive suction head required NPSHR. Cavitation can cause axial surging if it is excessive, will damage mechanical seals, bearings, possibly other pump components frequently and shorten the life of the impeller. Efforts have been made to explain Suction Energy (SE), Specific Speed (Ns), Suction Specific Speed (Nss), NPSHA, NPSHR & their significance, possible reasons of cavitation /internal re-circulation, its diagnostics and remedial measures to arrest and prevent cavitation in this paper. A case study is presented by the author highlighting that the root cause of unwanted noise and vibration is due to cavitation, caused by high specific speeds or inadequate net- positive suction head available which results in damages to material surfaces of impeller & suction bells and degradation of machine performance, its capacity and efficiency too. The author strongly recommends revisiting the technical specifications of CW pumps to provide sufficient NPSH margin ratios > 1.5, for future projects and Nss be limited to 8500 -9000 for cavitation free operation.

Keywords: best efficiency point (BEP), net positive suction head NPSHA, NPSHR, specific speed NS, suction specific speed NSS

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Authors: Kavyadevi N., Kaviya G., Gowsalya P., Janani M., Mohanraj S.

Abstract:

Hevea brasiliensis, also known as the rubber tree, is one of the foremost assets of crops in the world. One of the most significant advantages of the Rubber Plant in terms of air oxygenation is its capacity to reduce the likelihood of an individual developing respiratory allergies like asthma. To construct such a system that can properly identify crop diseases and pests and then create a database of insecticides for each pest and disease, we must first give treatment for the illness that has been detected. We shall primarily examine three major leaf diseases since they are economically deficient in this article, which is Bird's eye spot, algal spot and powdery mildew. And the recommended work focuses on disease identification on rubber tree leaves. It will be accomplished by employing one of the superior algorithms. Input, Preprocessing, Image Segmentation, Extraction Feature, and Classification will be followed by the processing technique. We will use time-consuming procedures that they use to detect the sickness. As a consequence, the main ailments, underlying causes, and signs and symptoms of diseases that harm the rubber tree are covered in this study.

Keywords: image processing, python, convolution neural network (CNN), machine learning

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Authors: Md Masihuddin Siddiqui, Abdul Haakim Mohammed

Abstract:

Earthquakes are the most unpredictable and devastating of all natural disasters. The behaviour of a building during an earthquake depends on several factors such as stiffness, adequate lateral strength, ductility, and configurations. The experience from the performance of buildings during past earthquakes has shown that the buildings with regular geometry, uniformly distributed mass and stiffness in plan as well as in elevation suffer much less damage compared to irregular configurations. The three centers namely- centre of mass, centre of strength, centre of stiffness are the torsional parameters which contribute to the strength of the building in case of an earthquake. Inertial forces and resistive forces in a structural system act through the center of mass and center of rigidity respectively which together oppose the forces that are produced during seismic excitation. So these centers of a structural system should be positioned where the structural system is the strongest so that the effects produced due to the earthquake may have a minimal effect on the structure. In this paper, the effects of variation of strength eccentricity and stiffness eccentricity in reducing the torsional responses of the asymmetrical buildings by using pushover analysis are studied. The maximum reduction of base torsion was observed in the case of minimum strength eccentricity, and the least reduction was observed in the case of minimum stiffness eccentricity.

Keywords: strength eccentricity, stiffness eccentricity, asymmetric structure, base torsion, push over analysis

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Authors: Azimollah Aleshzadeh, Enver Vural Yavuz

Abstract:

The main goal of this study is to produce landslide susceptibility maps using different data-driven bivariate statistical approaches; namely, entropy weight method (EWM), evidence belief function (EBF), and information content model (ICM), at Uzundere county, Erzurum province, in the north-eastern part of Turkey. Past landslide occurrences were identified and mapped from an interpretation of high-resolution satellite images, and earlier reports as well as by carrying out field surveys. In total, 42 landslide incidence polygons were mapped using ArcGIS 10.4.1 software and randomly split into a construction dataset 70 % (30 landslide incidences) for building the EWM, EBF, and ICM models and the remaining 30 % (12 landslides incidences) were used for verification purposes. Twelve layers of landslide-predisposing parameters were prepared, including total surface radiation, maximum relief, soil groups, standard curvature, distance to stream/river sites, distance to the road network, surface roughness, land use pattern, engineering geological rock group, topographical elevation, the orientation of slope, and terrain slope gradient. The relationships between the landslide-predisposing parameters and the landslide inventory map were determined using different statistical models (EWM, EBF, and ICM). The model results were validated with landslide incidences, which were not used during the model construction. In addition, receiver operating characteristic curves were applied, and the area under the curve (AUC) was determined for the different susceptibility maps using the success (construction data) and prediction (verification data) rate curves. The results revealed that the AUC for success rates are 0.7055, 0.7221, and 0.7368, while the prediction rates are 0.6811, 0.6997, and 0.7105 for EWM, EBF, and ICM models, respectively. Consequently, landslide susceptibility maps were classified into five susceptibility classes, including very low, low, moderate, high, and very high. Additionally, the portion of construction and verification landslides incidences in high and very high landslide susceptibility classes in each map was determined. The results showed that the EWM, EBF, and ICM models produced satisfactory accuracy. The obtained landslide susceptibility maps may be useful for future natural hazard mitigation studies and planning purposes for environmental protection.

Keywords: entropy weight method, evidence belief function, information content model, landslide susceptibility mapping

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Authors: Renee Moten

Abstract:

Introduction: Knee pain becomes chronic because the therapy used focuses only on the symptoms of knee pain and not the causes of knee pain. Preventing knee injuries is not in the toolbox of the traditional practitioner. This research was done to show that we must reduce the inflammation (holistically), reduce the swelling and regain flexibility before considering any type of exercise. This method of performing the correct exercise stops the bowing of the knee, corrects the walking gait, and starts to relieve knee, hip, back, and shoulder pain. Method: The holistic method that is used to heal knees is called the Knee Pain Recipe. It’s a six step system that only uses alternative medicine methods to reduce, relieve and restore knee joint mobility. The system is low cost, with no hospital bills, no physical therapy, and no painkillers that can cause damage to the kidneys and liver. This method has been tested on 200 women with knee, back, hip, and shoulder pain. Results: All 200 women reduce their knee pain by 50%, some by as much as 90%. Learning about ankle and foot flexibility, along with understanding the kinetic chain, helps improve the walking gait, which takes the pressure off the knee, hip and back. The knee pain recipe also has helped to reduce the need for a cortisone injection, stem cell procedures, to take painkillers, and surgeries. What has also been noted in the research was that if the women's knees were too far gone, the Knee Pain Recipe helped prepare the women for knee replacement surgery. Conclusion: It is believed that the Knee Pain Recipe, when performed by men and women from around the world, will give them a holistic alternative to drugs, injections, and surgeries.

Keywords: knee, surgery, healing, holistic

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